Wiley Interdisciplinary Reviews-Systems Biology and Medicine最新文献

Nowadays, mathematical modeling is playing a key role in many different research fields. In the context of system biology, mathematical models and their associated computer simulations constitute essential tools of investigation. Among the others, they provide a way to systematically analyze systems perturbations, develop hypotheses to guide the design of new experimental tests, and ultimately assess the suitability of specific molecules as novel therapeutic targets. To these purposes, stochastic simulation algorithms (SSAs) have been introduced for numerically simulating the time evolution of a well-stirred chemically reacting system by taking proper account of the randomness inherent in such a system. In this work, we review the main SSAs that have been introduced in the context of exact, approximate, and hybrid stochastic simulation. Specifically, we will introduce the direct method (DM), the first reaction method (FRM), the next reaction method (NRM) and the rejection-based SSA (RSSA) in the area of exact stochastic simulation. We will then present the τ-leaping method and the chemical Langevin method in the area of approximate stochastic simulation and an implementation of the hybrid RSSA (HRSSA) in the context of hybrid stochastic-deterministic simulation. Finally, we will consider the model of the sphingolipid metabolism to provide an example of application of SSA to computational system biology by exemplifying how different simulation strategies may unveil different insights into the investigated biological phenomenon. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Analytical and Computational Methods > Computational Methods.

Mathematical models and computer simulations have the great potential to substantially increase our understanding of the biophysical behavior of the neuromuscular system. This, however, requires detailed multiscale, and multiphysics models. Once validated, such models allow systematic in silico investigations that are not necessarily feasible within experiments and, therefore, have the ability to provide valuable insights into the complex interrelations within the healthy system and for pathological conditions. Most of the existing models focus on individual parts of the neuromuscular system and do not consider the neuromuscular system as an integrated physiological system. Hence, the aim of this advanced review is to facilitate the prospective development of detailed biophysical models of the entire neuromuscular system. For this purpose, this review is subdivided into three parts. The first part introduces the key anatomical and physiological aspects of the healthy neuromuscular system necessary for modeling the neuromuscular system. The second part provides an overview on state-of-the-art modeling approaches representing all major components of the neuromuscular system on different time and length scales. Within the last part, a specific multiscale neuromuscular system model is introduced. The integrated system model combines existing models of the motor neuron pool, of the sensory system and of a multiscale model describing the mechanical behavior of skeletal muscles. Since many sub-models are based on strictly biophysical modeling approaches, it closely represents the underlying physiological system and thus could be employed as starting point for further improvements and future developments. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models.

Agent-based modeling is a rule-based, discrete-event, and spatially explicit computational modeling method that employs computational objects that instantiate the rules and interactions among the individual components ("agents") of system. Agent-based modeling is well suited to translating into a computational model the knowledge generated from basic science research, particularly with respect to translating across scales the mechanisms of cellular behavior into aggregated cell population dynamics manifesting at the tissue and organ level. This capacity has made agent-based modeling an integral method in translational systems biology (TSB), an approach that uses multiscale dynamic computational modeling to explicitly represent disease processes in a clinically relevant fashion. The initial work in the early 2000s using agent-based models (ABMs) in TSB focused on examining acute inflammation and its intersection with wound healing; the decade since has seen vast growth in both the application of agent-based modeling to a wide array of disease processes as well as methodological advancements in the use and analysis of ABM. This report presents an update on an earlier review of ABMs in TSB and presents examples of exciting progress in the modeling of various organs and diseases that involve inflammation. This review also describes developments that integrate the use of ABMs with cutting-edge technologies such as high-performance computing, machine learning, and artificial intelligence, with a view toward the future integration of these methodologies. This article is categorized under: Translational, Genomic, and Systems Medicine > Translational Medicine Models of Systems Properties and Processes > Mechanistic Models Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Models of Systems Properties and Processes > Organismal Models.

Small arteries in the body control vascular resistance, and therefore, blood pressure and blood flow. Endothelial and smooth muscle cells in the arterial walls respond to various stimuli by altering the vascular resistance on a moment to moment basis. Smooth muscle cells can directly influence arterial diameter by contracting or relaxing, whereas endothelial cells that line the inner walls of the arteries modulate the contractile state of surrounding smooth muscle cells. Cytosolic calcium is a key driver of endothelial and smooth muscle cell functions. Cytosolic calcium can be increased either by calcium release from intracellular stores through IP3 or ryanodine receptors, or the influx of extracellular calcium through ion channels at the cell membrane. Depending on the cell type, spatial localization, source of a calcium signal, and the calcium-sensitive target activated, a particular calcium signal can dilate or constrict the arteries. Calcium signals in the vasculature can be classified into several types based on their source, kinetics, and spatial and temporal properties. The calcium signaling mechanisms in smooth muscle and endothelial cells have been extensively studied in the native or freshly isolated cells, therefore, this review is limited to the discussions of studies in native or freshly isolated cells. This article is categorized under: Biological Mechanisms > Cell Signaling Laboratory Methods and Technologies > Imaging Models of Systems Properties and Processes > Mechanistic Models.

The circadian clock is a molecular endogenous timekeeping system and allows organisms to adjust their physiology and behavior to the geophysical time. Organized hierarchically, the master clock in the suprachiasmatic nuclei, coordinates peripheral clocks, via direct, or indirect signals. In peripheral organs, such as the liver, the circadian clock coordinates gene expression, notably metabolic gene expression, from transcriptional to posttranslational level. The metabolism in return feeds back on the molecular circadian clock via posttranslational-based mechanisms. During the last two decades, circadian gene expression studies have mostly been relying primarily on genomics or transcriptomics approaches and transcriptome analyses of multiple organs/tissues have revealed that the majority of protein-coding genes display circadian rhythms in a tissue specific manner. More recently, new advances in mass spectrometry offered circadian proteomics new perspectives, that is, the possibilities of performing large scale proteomic studies at cellular and subcellular levels, but also at the posttranslational modification level. With important implications in metabolic health, cell signaling has been shown to be highly relevant to circadian rhythms. Moreover, comprehensive characterization studies of posttranslational modifications are emerging and as a result, cell signaling processes are expected to be more deeply characterized and understood in the coming years with the use of proteomics. This review summarizes the work studying diurnally rhythmic or circadian gene expression performed at the protein level. Based on the knowledge brought by circadian proteomics studies, this review will also discuss the role of posttranslational modification events as an important link between the molecular circadian clock and metabolic regulation. This article is categorized under: Laboratory Methods and Technologies > Proteomics Methods Physiology > Mammalian Physiology in Health and Disease Biological Mechanisms > Cell Signaling.

Microglia are the specialized macrophages of the brain and play essential roles in ensuring its proper functioning. Accumulating evidence suggests that these cells coordinate the inflammatory response that accompanies various clinical brain conditions, including neurodegenerative diseases and psychiatric disorders. Therefore, investigating the functions of these cells and how these are regulated have become important areas of research in neuroscience over the past decade. In this regards, recent efforts to characterize the epigenomic mechanisms underlying microglial gene transcription have provided significant insights into the mechanisms that control the ontogeny and the cellular competences of microglia. In particular, these studies have established that a substantial proportion of the microglial repertoire of promoter-distal genomic regulatory elements, or enhancers, is relatively specific to these cells compared to other tissue-resident macrophages. Notably, this specificity is under the regulation of factors present in the brain that modulate activity of target axes of signaling pathways-transcription factors in microglia. Thus, the microglial enhancer repertoire is highly responsive to perturbations in the cerebral tissue microenvironment and this responsiveness has profound implications on the activity of these cells in brain diseases. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Mechanistic Models Biological Mechanisms > Cell Fates Developmental Biology > Lineages.

Interleukin-7 (IL7) plays a nonredundant role in T cell survival and homeostasis, which is illustrated in the severe T cell lymphopenia of IL7-deficient mice, or demonstrated in animals or humans that lack expression of either the IL7Rα or γ _c chain, the two subunits that constitute the functional IL7 receptor. Remarkably, IL7 is not expressed by T cells themselves, but produced in limited amounts by radio-resistant stromal cells. Thus, T cells need to constantly compete for IL7 to survive. How T cells maintain homeostasis and further maximize the size of the peripheral T cell pool in face of such competition are important questions that have fascinated both immunologists and mathematicians for a long time. Exceptionally, IL7 downregulates expression of its own receptor, so that IL7-signaled T cells do not consume extracellular IL7, and thus, the remaining extracellular IL7 can be shared among unsignaled T cells. Such an altruistic behavior of the IL7Rα chain is quite unique among members of the γ _c cytokine receptor family. However, the consequences of this altruistic signaling behavior at the molecular, single cell and population levels are less well understood and require further investigation. In this regard, mathematical modeling of how a limited resource can be shared, while maintaining the clonal diversity of the T cell pool, can help decipher the molecular or cellular mechanisms that regulate T cell homeostasis. Thus, the current review aims to provide a mathematical modeling perspective of IL7-dependent T cell homeostasis at the molecular, cellular and population levels, in the context of recent advances in our understanding of the IL7 biology. This article is categorized under: Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Biological Mechanisms > Cell Signaling Models of Systems Properties and Processes > Mechanistic Models Analytical and Computational Methods > Computational Methods.